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Daniel Levine

2 accepted papers

2025

Non-Markovian Discrete Diffusion with Causal Language Models

NeurIPS 2025poster

Discrete diffusion models offer a flexible, controllable approach to structured sequence generation, yet they still lag behind causal language models in expressive power. A key limitation lies in their reliance on the Markovian assumption, which restricts each step to condition only on the current s…

Cited by 0SourceScholar
2024

Cell2Sentence: Teaching Large Language Models the Language of Biology

ICML 2024poster

We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into "cell sentences," C2S bridges the gap between natural language processing and biology. We demonstrate…

Cited by 19SourcePDFScholar